What's basic about basic emotions?

Comparing competing characterizations suggests there might be more than one type of interest

Although there is general consensus concerning the importance and function of interest in our daily lives, there is little agreement about its nature. Four studies of increasing ecological validity (total N = 993) were carried out to compare two different characterizations of interest in terms of the key appraisals involved. The findings indicate that while a two-appraisal model is suitable to explain the interest we can feel towards simple stimuli, a more complex model may better capture the nature of interest in the real world. Further analysis suggested the contrasting previous results could be resolved by arguing that previous models of interest capture different types of interest. This novel finding represents a promising first step towards a more definitive definition of interest, and suggests that while interest may always be related to motivating exploration, learning and general well-being, researchers should be more precise about the type of interest to which they refer.

Social Anxiety Symptoms Predict Poorer Facial Emotion Recognition in Autistic Male Adolescents and Young Adults Without Intellectual Disability

Utilizing a novel computerized task, we aimed to examine whether social anxiety symptoms would be related to individual differences in facial emotion recognition (FER) in a sample of autistic male adolescents and young adults without intellectual disability. Results indicated that social anxiety and IQ predicted poorer FER, irrespective of specific emotion type. When probing specific effects within emotion and condition types, social anxiety impacted surprise and disgust FER during a truncated viewing condition and not full viewing condition. Collectively, results suggest that social anxiety in autism may play a larger role in FER than previously thought. Future work should consider the role of social anxiety within autism as a factor that may meaningfully relate to FER assessment and intervention.

Emotional Prototypicality Ratings for 636 Chinese Words: A Database of Chinese Words with Affective Information

Exemplars of concepts vary in their degree of prototypicality. This is also true for emotion concepts. This study presents prototypicality ratings for a large set of Chinese words. The database contains 636 potential Chinese emotion words (i.e., words that directly express particular emotions, like " happy" and " sad"), from different grammatical categories. Native Chinese speakers rated the words in terms of emotional prototypicality. The database also contains values for valence, arousal, and emotionality. The analyses of the ratings revealed that 502 out of 636 words had a high prototypicality value (value equal to or above three on a 1-to-5 scale), the most prototypical words being negative and high-arousal words. The analyses also indicated that the emotional prototypicality of a word was positively related to both arousal and emotionality, and negatively related to valence. Among these variables, arousal was the most important contributor. Similar results have been found in studies conducted in other languages. This will be a useful resource for researchers interested in studying emotion words in the Chinese language and for those interested in cross-linguistic comparisons.

Learning emotional dialects: A British population study of cross-cultural communication

The aim of the current research was to explore whether we can improve the recognition of cross-cultural freely-expressed emotional faces in British participants. We tested several methods for improving the recognition of freely-expressed emotional faces, such as different methods for presenting other-culture expressions of emotion from individuals from Chile, New Zealand and Singapore in two experimental stages. In the first experimental stage, in phase one, participants were asked to identify the emotion of cross-cultural freely-expressed faces. In the second phase, different cohorts were presented with interactive side-by-side, back-to-back and dynamic morphing of cross-cultural freely-expressed emotional faces, and control conditions. In the final phase, we repeated phase one using novel stimuli. We found that all non-control conditions led to recognition improvements. Morphing was the most effective condition for improving the recognition of cross-cultural emotional faces. In the second experimental stage, we presented morphing to different cohorts including own-to-other and other-to-own freely-expressed cross-cultural emotional faces and neutral-to-emotional and emotional-to-neutral other-culture freely-expressed emotional faces. All conditions led to recognition improvements and the presentation of freely-expressed own-to-other cultural-emotional faces provided the most effective learning. These findings suggest that training can improve the recognition of cross-cultural freely-expressed emotional expressions.

Using social media and personality traits to assess software developers' emotional polarity

Although human factors (e.g., cognitive functions, behaviors and skills, human error models, etc.) are key elements to improve software development productivity and quality, the role of software developers' emotions and their personality traits in software engineering still needs to be studied. A major difficulty is in assessing developers' emotions, leading to the classic problem of having difficulties understanding what cannot be easily measured. Existing approaches to infer emotions, such as facial expressions, self-assessed surveys, and biometric sensors, imply considerable intrusiveness on developers and tend to be used only during normal working periods. This article proposes to assess the feasibility of using social media posts (e.g., developers' posts on Twitter) to accurately determine the polarity of emotions of software developers over extended periods in a non-intrusive manner, allowing the identification of potentially abnormal periods of negative or positive sentiments of developers that may affect software development productivity or software quality. Our results suggested that Twitter data can serve as a valid source for accurately inferring the polarity of emotions. We evaluated 31 combinations of unsupervised lexicon-based techniques using a dataset with 79,029 public posts from Twitter from sixteen software developers, achieving a macro F1-Score of 0.745 and 76.8% of accuracy with the ensemble comprised of SentiStrength, Sentilex-PT, and LIWC2015_PT lexicons. Among other results, we found a statistically significant difference in tweets' polarities posted during working and non-working periods for 31.25% of the participants, suggesting that emotional polarity monitoring outside working hours could also be relevant. We also assessed the Big Five personality traits of the developers and preliminarily used them to ponder the polarities inferences. In this context, Openness, Conscientiousness, and Extraversion were frequently related to neutral and positive posts, while Neuroticism is associated with negative posts. Our results show that the proposed approach is accurate enough to constitute a simple and non-intrusive alternative to existing methods. Tools using this approach can be applied in real software development environments to support software team workers in making decisions to improve the software development process.

Facial Expressions as an Index of Listening Difficulty and Emotional Response

Knowledge about listening difficulty experienced during a task can be used to better understand speech perception processes, to guide amplification outcomes, and can be used by individuals to decide whether to participate in communication. Another factor affecting these decisions is individuals' emotional response which has not been measured objectively previously. In this study, we describe a novel method of measuring listening difficulty and affect of individuals in adverse listening situations using automatic facial expression algorithm. The purpose of our study was to determine if facial expressions of confusion and frustration are sensitive to changes in listening difficulty. We recorded speech recognition scores, facial expressions, subjective listening effort scores, and subjective emotional responses in 33 young participants with normal hearing. We used the signal-to-noise ratios of -1, +2, and +5 dB SNR and quiet conditions to vary the difficulty level. We found that facial expression of confusion and frustration increased with increase in difficulty level, but not with change in each level. We also found a relationship between facial expressions and both subjective emotion ratings and subjective listening effort. Emotional responses in the form of facial expressions show promise as a measure of affect and listening difficulty. Further research is needed to determine the specific contribution of affect to communication in challenging listening environments.

Revisiting emotion recognition in different types of temporal lobe epilepsy: The influence of facial expression intensity

Temporal lobe epilepsy (TLE) can induce various difficulties in recognizing emotional facial expressions (EFE), particularly for negative valence emotions. However, these difficulties have not been systematically examined according to the localization of the epileptic focus. For this purpose, we used a forced-choice recognition task in which faces expressing fear, sadness, anger, disgust, surprise, or happiness were presented in different intensity levels from moderate to high intensity. The first objective of our study was to evaluate the impact of emotional intensity on the recognition of different categories of EFE in TLE patients compared to control participants. The second objective was to assess the effect of localizationof epileptic focus on the recognition of EFE in patients with medial temporal lobe epilepsy (MTLE) associated or not with hippocampal sclerosis (HS), or lateral temporal lobe epilepsy (LTLE). The results showed that the 272 TLE patients and the 68 control participants were not differently affected by the intensity of EFE. However, we obtained group differences within the clinical population when we took into account the localization of the temporal lobe epileptic focus. As predicted, TLE patients were impaired in recognizing fear and disgust relative to controls. Moreover, the scores of these patients varied according to the localization of the epileptic focus, but not according to the cerebral lateralization of TLE. The facial expression of fear was less well recognized by MTLE patients, with or without HS, and the expression of disgust was less well recognized by LTLE as well as MTLE without HS patients. Moreover, emotional intensity modulated differently the recognition of disgust and surprise of the three patient groups underlying the relevance of using moderate emotional intensity to distinguish the effect of epileptic focus localization. These findings should be taken into account for interpreting the emotional behaviors and deserve to befurther investigated before considering TLE surgical treatment or social cognition interventions in TLE patients.

The taste & affect music database: Subjective rating norms for a new set of musical stimuli

Music is a ubiquitous stimulus known to influence human affect, cognition, and behavior. In the context of eating behavior, music has been associated with food choice, intake and, more recently, taste perception. In the latter case, the literature has reported consistent patterns of association between auditory and gustatory attributes, suggesting that individuals reliably recognize taste attributes in musical stimuli. This study presents subjective norms for a new set of 100 instrumental music stimuli, including basic taste correspondences (sweetness, bitterness, saltiness, sourness), emotions (joy, anger, sadness, fear, surprise), familiarity, valence, and arousal. This stimulus set was evaluated by 329 individuals (83.3% women; Mage = 28.12, SD = 12.14), online (n = 246) and in the lab (n = 83). Each participant evaluated a random subsample of 25 soundtracks and responded to self-report measures of mood and taste preferences, as well as the Goldsmiths Musical Sophistication Index (Gold-MSI). Each soundtrack was evaluated by 68 to 97 participants (Mdn = 83), and descriptive results (means, standard deviations, and confidence intervals) are available as supplemental material at osf.io/2cqa5 . Significant correlations between taste correspondences and emotional/affective dimensions were observed (e.g., between sweetness ratings and pleasant emotions). Sex, age, musical sophistication, and basic taste preferences presented few, small to medium associations with the evaluations of the stimuli. Overall, these results suggest that the new Taste & Affect Music Database is a relevant resource for research and intervention with musical stimuli in the context of crossmodal taste perception and other affective, cognitive, and behavioral domains.

Emotions in social anxiety disorder: A review

Extant cognitive behavioral models of social anxiety disorder (SAD) have primarily focused on cognitions and behaviors that maintain the disorder. Emotional aspects of SAD have been investigated but have not been sufficiently integrated into current models. To facilitate such integration, we reviewed the literature on emotional constructs (emotional intelligence, emotional knowledge, emotional clarity, emotion differentiation, and emotion regulation), and discrete emotions (anger, shame, embarrassment, loneliness, guilt, pride, and envy) in SAD and social anxiety. We present the studies conducted on these constructs, summarize the main findings, suggest areas for future research, discuss the findings in the context of existing models of SAD and attempt to integrate the findings into these existing models of the disorder. Clinical implications of our findings are also discussed.

Perception and classification of emotions in nonsense speech: Humans versus machines

This article contributes to a more adequate modelling of emotions encoded in speech, by addressing four fallacies prevalent in traditional affective computing: First, studies concentrate on few emotions and disregard all other ones ('closed world'). Second, studies use clean (lab) data or real-life ones but do not compare clean and noisy data in a comparable setting ('clean world'). Third, machine learning approaches need large amounts of data; however, their performance has not yet been assessed by systematically comparing different approaches and different sizes of databases ('small world'). Fourth, although human annotations of emotion constitute the basis for automatic classification, human perception and machine classification have not yet been compared on a strict basis ('one world'). Finally, we deal with the intrinsic ambiguities of emotions by interpreting the confusions between categories ('fuzzy world'). We use acted nonsense speech from the GEMEP corpus, emotional 'distractors' as categories not entailed in the test set, real-life noises that mask the clear recordings, and different sizes of the training set for machine learning. We show that machine learning based on state-of-the-art feature representations (wav2vec2) is able to mirror the main emotional categories ('pillars') present in perceptual emotional constellations even in degradated acoustic conditions.

Dual-Language Testing of Emotional Verbal Fluency: A Closer Look at "Joy," "Sadness," "Fear," "Anger," and "Disgust"

OBJECTIVE

Assessing neuropsychological functions of dual-language speakers with semantic verbal fluency should consider the impact of language proficiency. Much evidence for the proficiency effect is found in tasks targeting neutral words. The proficiency effect on emotional verbal fluency (Emo-VF) that targets emotional word retrieval, however, is far from conclusive. This study aimed to clarify the proficiency effect on Emo-VF, specifically the extent to which language proficiency impacted positive and negative word retrieval comparably. In addition, the study examined the extent to which dual-languages speakers produced duplicated items and unique, non-duplicated items in each of two languages tested.

METHOD

Thirty-two adult participants completed Emo-VF tasks that targeted a comprehensive set of basic emotions ("joy," "sadness," "fear," "anger," "disgust") in English and Spanish in two sessions separated by at least 72 h. All participants exhibited greater proficiency in English than in Spanish according to subjective and objective measures of language proficiency.

RESULTS

Verbal productivity was comparably lowered for all emotions in the less proficient language. Differences among categories were consistent between languages, with "joy" eliciting more words than other emotions, and "fear" yielding the highest productivity among negative emotions. Finally, dual-language speakers produced a significant number of unique items in different languages, especially for "fear."

CONCLUSION

Language proficiency exerts a general effect on positive and negative word retrieval. The study extends previous work by revealing differences between "fear" and other negative categories in addition to replicating positivity biases in unbalanced dual-language speakers. Dual-language testing is valuable in capturing the richness of emotional word repertoire associated with different languages.

Exploring effects of response biases in affect induction procedures

This study examined whether self-reports or ratings of experienced affect, often used as manipulation checks on the efficacy of affect induction procedures (AIPs), reflect genuine changes in affective states rather than response biases arising from demand characteristics or social desirability effects. In a between-participants design, participants were exposed to positive, negative and neutral images with valence-congruent music or sound to induce happy, sad and neutral mood. Half of the participants had to actively appraise each image whereas the other half viewed images passively. We hypothesised that if ratings of affective valence are subject to response biases then they should reflect the target mood in the same way for active appraisal and passive exposure as participants encountered the same affective stimuli in both conditions. We also tested whether the AIP resulted in mood-congruent changes in facial expressions analysed by FaceReader to see whether behavioural indicators corroborate the self-reports. The results showed that while participants' ratings reflected the induced target valence, the difference between positive and negative AIP was significantly attenuated in the active appraisal condition, suggesting that self-reports of mood experienced after the AIP are not entirely a reflection of response biases. However, there were no effects of the AIP on FaceReader valence scores, in line with theories questioning the existence of cross-culturally and inter-individually universal behavioural indicators of affective states. Efficacy of AIPs is therefore best checked using self-reports.

Maternal Anxiety and Its Associated Factors During the First and Second Wave of COVID-19 Pandemic in Serbia: A Cross-Sectional Study

Aim

The COVID 19-pandemic affects people differently, while pregnant women are among the most sensitive populations. The data about maternal mental health during the COVID-19 outbreak are in some ways consistent but also country-specific.

Purpose

The study aims to explore the impact of the COVID-19 pandemic on pregnant women's anxiety and identify its associated factors.

Patients and Methods

This cross-sectional study included a sample of 358 pregnant women during the first and second waves of the pandemic in Serbia. An anonymous survey included basic demographic questions, pregnancy-related background questions, the question of self-reported COVID-19-related fear, State-Trait Anxiety Inventory (STAI), and Multidimensional Scale of Perceived Social Support (MSPSS).

Results

The study revealed no pregnant women with low anxiety levels measured by STAI-T and STAI-S, while the STAI-S and STAI-T scores indicated high anxiety in 32.4% and 42.7% of pregnant women, respectively. The obtained results pointed out the nonlinear dependence of state anxiety on observed associated factors and their complex interactions, including the data collecting period.

Conclusion

Our findings reveal that COVID-19 affects pregnant women's mental health and makes it necessary for psychological monitoring and support for pregnant women, which may be reflected in their mental health but also the development of their offspring.

A Survey on Affective and Cognitive VR

In Virtual Reality (VR), users can be immersed in emotionally intense and cognitively engaging experiences. Yet, despite strong interest from scholars and a large amount of work associating VR and Affective and Cognitive States (ACS), there is a clear lack of structured and systematic form in which this research can be classified. We define "Affective and Cognitive VR" to relate to works which (1) induce ACS, (2) recognize ACS, or (3) exploit ACS by adapting virtual environments based on ACS measures. This survey clarifies the different models of ACS, presents the methods for measuring them with their respective advantages and drawbacks in VR, and showcases Affective and Cognitive VR studies done in an Immersive Virtual Environment (IVE) in a non-clinical context. Our article covers the main research lines in Affective and Cognitive VR. We provide a comprehensive list of references with the analysis of 63 research articles and summarize future works directions.

Surprise as an Emotion: A Response to Ortony

We write in response to an article published in this journal by Andrew Ortony titled “Are All ‘Basic Emotions’ Emotions? A Problem for the (Basic) Emotions Construct.” The author claimed that “for all its elevated status as a basic emotion, surprise fails to satisfy the minimal requirements that [he] proposed for something to be an emotion, and if it is not an emotion, it cannot possibly be a basic emotion.” Although we acknowledge the concerns brought forth by Ortony, we respectfully disagree with his conclusion about surprise. To make a case against the assertion that surprise is valence-free, we summarize an extensive body of work showing that surprise is indeed valenced—in a specific manner (i.e., ambiguously valenced)—and that it meets all of Ortony’s criteria for an emotion. In other words, rather than being described as neither positive nor negative, this emotion is either positive or negative. We consider the data with respect to surprise as a basic emotion, and we dispute the definitions of basic emotions as “widely divergent.” Future work is needed to continue defining an emotion, and a basic emotion, but we believe this is a worthy effort toward shaping a still evolving field.

Caregivers' perceptions of informal social control practices to reduce child neglect: A qualitative study in Ghana

BACKGROUND

Rational choice deterrence theory suggests that caregiving behavior, which includes abusive and neglectful behavior, can be influenced or manipulated via informal social control strategies enacted by neighbors, family members and friends in the social network. The literature identifies two forms of informal social control that have the potential to influence maltreating caregiver behavior, protective vs punitive, with the latter having more contrasting evidence related to its influence on maltreating caregiving practices.

OBJECTIVE

To examine the perceptions and meanings female caregivers associate with protective and punitive informal social control strategies that have been enacted against them.

METHODS

17 female caregivers from Ghana, who self-reported their involvement in neglectful acts, were purposively selected to engage in river of life oral history narrative interviews. Narrative accounts from the caregivers were analyzed thematically using Taguette software package.

RESULTS

The findings showed that protective informal social control in child neglect are interpreted via values and norms of childcare that have been institutionalized in the community. Caregivers perceived protective informal social control to have impact on their level of respect/influence, authority in the family or community, and to elicit internal consequences: shame, guilty feelings and embarrassment. Punitive informal social control approaches were considered as misplaced interventions that had ulterior motives of satisfying the neighbors' hatred/dislike of the perpetrator and quest for revenge.

CONCLUSION

The findings suggest that the development of a fruitful theoretical framework to explain the effectiveness of informal social control should prioritize the social values and legitimate norms of the community. Implications for practice and theory development are discussed.

Monoamine Neurotransmitters Control Basic Emotions and Affect Major Depressive Disorders

Major depressive disorder (MDD) is a common and complex mental disorder, that adversely impacts an individual’s quality of life, but its diagnosis and treatment are not accurately executed and a symptom-based approach is utilized in most cases, due to the lack of precise knowledge regarding the pathophysiology. So far, the first-line treatments are still based on monoamine neurotransmitters. Even though there is a lot of progress in this field, the mechanisms seem to get more and more confusing, and the treatment is also getting more and more controversial. In this study, we try to review the broad advances of monoamine neurotransmitters in the field of MDD, and update its effects in many advanced neuroscience studies. We still propose the monoamine hypothesis but paid special attention to their effects on the new pathways for MDD, such as inflammation, oxidative stress, neurotrophins, and neurogenesis, especially in the glial cells, which have recently been found to play an important role in many neurodegenerative disorders, including MDD. In addition, we will extend the monoamine hypothesis to basic emotions; as suggested in our previous reports, the three monoamine neurotransmitters play different roles in emotions: dopamine—joy, norepinephrine—fear (anger), serotonins—disgust (sadness). Above all, this paper tries to give a full picture of the relationship between the MDD and the monoamine neurotransmitters such as DA, NE, and 5-HT, as well as their contributions to the Three Primary Color Model of Basic Emotions (joy, fear, and disgust). This is done by explaining the contribution of the monoamine from many sides for MDD, such the digestive tract, astrocytes, microglial, and others, and very briefly addressing the potential of monoamine neurotransmitters as a therapeutic approach for MDD patients and also the reasons for its limited clinical efficacy, side effects, and delayed onset of action. We hope this review might offer new pharmacological management of MDD.

How facial masks alter the interaction of gaze direction, head orientation, and emotion recognition

The COVID-19 pandemic has altered the way we interact with each other: mandatory mask-wearing obscures facial information that is crucial for emotion recognition. Whereas the influence of wearing a mask on emotion recognition has been repeatedly investigated, little is known about the impact on interaction effects among emotional signals and other social signals. Therefore, the current study sought to explore how gaze direction, head orientation, and emotional expression interact with respect to emotion perception, and how these interactions are altered by wearing a face mask. In two online experiments, we presented face stimuli from the Radboud Faces Database displaying different facial expressions (anger, fear, happiness, neutral, and sadness), gaze directions (−13°, 0°, and 13°), and head orientations (−45°, 0°, and 45°) – either without (Experiment 1) or with mask (Experiment 2). Participants categorized the displayed emotional expressions. Not surprisingly, masks impaired emotion recognition. Surprisingly, without the mask, emotion recognition was unaffected by averted head orientations and only slightly affected by gaze direction. The mask strongly interfered with this ability. The mask increased the influence of head orientation and gaze direction, in particular for the emotions that were poorly recognized with mask. The results suggest that in case of uncertainty due to ambiguity or absence of signals, we seem to unconsciously factor in extraneous information.

Emotion Elicitation through Vibrotactile Stimulation as an Alternative for Deaf and Hard of Hearing People: An EEG Study

Despite technological and accessibility advances, the performing arts and their cultural offerings remain inaccessible to many people. By using vibrotactile stimulation as an alternative channel, we explored a different way to enhance emotional processes produced while watching audiovisual media and, thus, elicit a greater emotional reaction in hearing-impaired people. We recorded the brain activity of 35 participants with normal hearing and 8 participants with severe and total hearing loss. The results showed activation in the same areas both in participants with normal hearing while watching a video, and in hearing-impaired participants while watching the same video with synchronized soft vibrotactile stimulation in both hands, based on a proprietary stimulation glove. These brain areas (bilateral middle frontal orbitofrontal, bilateral superior frontal gyrus, and left cingulum) have been reported as emotional and attentional areas. We conclude that vibrotactile stimulation can elicit the appropriate cortex activation while watching audiovisual media.

Automated Affective Computing Based on Bio-Signals Analysis and Deep Learning Approach

Extensive possibilities of applications have rendered emotion recognition ineluctable and challenging in the fields of computer science as well as in human-machine interaction and affective computing. Fields that, in turn, are increasingly requiring real-time applications or interactions in everyday life scenarios. However, while extremely desirable, an accurate and automated emotion classification approach remains a challenging issue. To this end, this study presents an automated emotion recognition model based on easily accessible physiological signals and deep learning (DL) approaches. As a DL algorithm, a Feedforward Neural Network was employed in this study. The network outcome was further compared with canonical machine learning algorithms such as random forest (RF). The developed DL model relied on the combined use of wearables and contactless technologies, such as thermal infrared imaging. Such a model is able to classify the emotional state into four classes, derived from the linear combination of valence and arousal (referring to the circumplex model of affect’s four-quadrant structure) with an overall accuracy of 70% outperforming the 66% accuracy reached by the RF model. Considering the ecological and agile nature of the technique used the proposed model could lead to innovative applications in the affective computing field.

Hybrid deep convolutional model-based emotion recognition using multiple physiological signals

Emotion recognition has become increasingly utilized in the medical, advertising, and military domains. Recognizing the cues of emotion from human behaviors or physiological responses is encouraging for the research community. However, extracting true characteristics from sensor data to understand emotions can be challenging due to the complex nature of these signals. Therefore, advanced feature engineering techniques are required for accurate signal recognition. This study presents a hybrid affective model that employs a transfer learning approach for emotion classification using large-frame sensor signals which employ a genuine dataset of signal fusion gathered from 30 participants using wearable sensor systems interconnected with mobile devices. The proposed approach implements several learning algorithms such as Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Recurrent Neural Network (RNN), and several other shallow methods on the sensor input to handle the requirements for the traditional feature extraction process. The findings reveal that the use of deep learning methods is satisfactory in affect recognition when a great number of frames is employed, and the proposed hybrid deep model outperforms traditional neural network (overall accuracy of 54%) and deep learning approaches (overall accuracy of 76%), with an average classification accuracy of 93%. This hybrid deep model also has a higher accuracy than our previously proposed statistical autoregressive hidden Markov model (AR-HMM) approach, with 88.6% accuracy. Accuracy assessment was performed by means of several statistics measures (accuracy, precision, recall, F-measure, and RMSE).

How does the presence of a surgical face mask impair the perceived intensity of facial emotions?

The use of surgical-type face masks has become increasingly common during the COVID-19 pandemic. Recent findings suggest that it is harder to categorise the facial expressions of masked faces, than of unmasked faces. To date, studies of the effects of mask-wearing on emotion recognition have used categorisation paradigms: authors have presented facial expression stimuli and examined participants’ ability to attach the correct label (e.g., happiness, disgust). While the ability to categorise particular expressions is important, this approach overlooks the fact that expression intensity is also informative during social interaction. For example, when predicting an interactant’s future behaviour, it is useful to know whether they are slightly fearful or terrified, contented or very happy, slightly annoyed or angry. Moreover, because categorisation paradigms force observers to pick a single label to describe their percept, any additional dimensionality within observers’ interpretation is lost. In the present study, we adopted a complementary emotion-intensity rating paradigm to study the effects of mask-wearing on expression interpretation. In an online experiment with 120 participants (82 female), we investigated how the presence of face masks affects the perceived emotional profile of prototypical expressions of happiness, sadness, anger, fear, disgust, and surprise. For each of these facial expressions, we measured the perceived intensity of all six emotions. We found that the perceived intensity of intended emotions (i.e., the emotion that the actor intended to convey) was reduced by the presence of a mask for all expressions except for anger. Additionally, when viewing all expressions except surprise, masks increased the perceived intensity of non-intended emotions (i.e., emotions that the actor did not intend to convey). Intensity ratings were unaffected by presentation duration (500ms vs 3000ms), or attitudes towards mask wearing. These findings shed light on the ambiguity that arises when interpreting the facial expressions of masked faces.

A Narrative Case Study of Chinese Senior High School English Teachers' Emotions: An Ecological Perspective

Teacher emotion research is of great significance to teachers’ teaching effectiveness, professional development, and physical and mental health. Taken from an ecological perspective, this narrative case study used purposeful sampling to select two Chinese senior high school English teachers as research participants. Various data collection methods were used, including narrative framework, teacher interview and teacher reflection log, to describe the emotional episodes of Chinese senior high school English teachers before and after collective lesson presentation, trial teaching, and formal teaching in a teaching improvement project. The purpose of this collection of data was to explore the dynamic emotional development process and characteristics of Chinese senior high school English teachers in the interaction with ecological systems and those ecological factors that may influence their emotional development. Results indicated that the two participants developed 68 emotions: 39 positive and 29 negative emotions. At exosystem, they developed the most emotions (28 emotions). Teacher emotion changed with time quite obviously. They evolved from positive to negative and, finally, predominantly positive. Personal antecedents, contextual antecedents, and teachers’ emotional capacity are the main ecological factors that may influence the development of teacher emotion. Based on the research findings, implications for teachers’ professional development and teacher education were also provided.

Who's Getting a Head Start? Mesocephalic Dogs in Still Images Are Attributed More Positively Valenced Emotions Than Dogs of Other Cephalic Index Groups

Assumptions about dogs' personality are influenced by their appearance, which may lead to differences in ownership styles and subsequent canine welfare. The influence of canine appearance on observers' emotion attributions to dogs remains largely unexplored. This study investigated whether canine head shape is related to how both dog owners and non-dog owning adults in the U.K. attribute emotions to still images of dogs, and in the case of dog owners, to their own dogs. Attachment, respondent personality and dog trainability were assessed as potential influences on emotional attribution in owners. Overall, 2451 participant responses were received. Still images of mesocephalic dogs were attributed primary and positively valenced emotion with more strength and frequency than other groups. Mesocephalic images were also attributed negatively valenced emotions less frequently and with less strength than other groups. Apart from empathy, no significant differences were found in emotional attribution to owned dogs of different head shapes; however, human personality influenced attribution of emotions to owned dogs. The finding that some dogs are attributed emotions more readily based on their appearance alone has applied importance, given, for example, the potential for misattribution of positive emotions to dogs in negative emotional states, and potential prejudice against dogs considered in negative emotional states.

Emotion norms for 6000 Polish word meanings with a direct mapping to the Polish wordnet

Emotion lexicons are useful in research across various disciplines, but the availability of such resources remains limited for most languages. While existing emotion lexicons typically comprise words, it is a particular meaning of a word (rather than the word itself) that conveys emotion. To mitigate this issue, we present the Emotion Meanings dataset, a novel dataset of 6000 Polish word meanings. The word meanings are derived from the Polish wordnet (plWordNet), a large semantic network interlinking words by means of lexical and conceptual relations. The word meanings were manually rated for valence and arousal, along with a variety of basic emotion categories (anger, disgust, fear, sadness, anticipation, happiness, surprise, and trust). The annotations were found to be highly reliable, as demonstrated by the similarity between data collected in two independent samples: unsupervised (n = 21,317) and supervised (n = 561). Although we found the annotations to be relatively stable for female, male, younger, and older participants, we share both summary data and individual data to enable emotion research on different demographically specific subgroups. The word meanings are further accompanied by the relevant metadata, derived from open-source linguistic resources. Direct mapping to Princeton WordNet makes the dataset suitable for research on multiple languages. Altogether, this dataset provides a versatile resource that can be employed for emotion research in psychology, cognitive science, psycholinguistics, computational linguistics, and natural language processing.

The Psychological Construction of Emotion – A Non-Essentialist Philosophy of Science

Advocates for the psychological construction of emotion view themselves as articulating a non-essentialist alternative to basic emotion theory's essentialist notion of affect programs. Psychological constructionists have also argued that holding essentialist assumptions about emotions engenders misconceptions about the psychological constructionist viewpoint. If so, it is important to understand what psychological constructionists mean by “essentialism” and “non-essentialism.” To advance the debate, I take a deeper dive into non-essentialism, comparing the non-essentialist views of the early empiricists with those of the psychological constructionists, focusing on the theories of James Russell and Lisa Barrett. Using Lakatos’ notion of scientific research programs, I also describe how Russell's and Barrett's views have evolved into different and potentially competing research programs under the psychological constructionist banner.

"There Is No (Where a) Face Like Home": Recognition and Appraisal Responses to Masked Facial Dialects of Emotion in Four Different National Cultures

The theory of universal emotions suggests that certain emotions such as fear, anger, disgust, sadness, surprise and happiness can be encountered cross-culturally. These emotions are expressed using specific facial movements that enable human communication. More recently, theoretical and empirical models have been used to propose that universal emotions could be expressed via discretely different facial movements in different cultures due to the non-convergent social evolution that takes place in different geographical areas. This has prompted the consideration that own-culture emotional faces have distinct evolutionary important sociobiological value and can be processed automatically, and without conscious awareness. In this paper, we tested this hypothesis using backward masking. We showed, in two different experiments per country of origin, to participants in Britain, Chile, New Zealand and Singapore, backward masked own and other-culture emotional faces. We assessed detection and recognition performance, and self-reports for emotionality and familiarity. We presented thorough cross-cultural experimental evidence that when using Bayesian assessment of non-parametric receiver operating characteristics and hit-versus-miss detection and recognition response analyses, masked faces showing own cultural dialects of emotion were rated higher for emotionality and familiarity compared to other-culture emotional faces and that this effect involved conscious awareness.

Prediction of Communication Effectiveness During Media Skills Training Using Commercial Automatic Non-verbal Recognition Systems

It is well recognised that social signals play an important role in communication effectiveness. Observation of videos to understand non-verbal behaviour is time-consuming and limits the potential to incorporate detailed and accurate feedback of this behaviour in practical applications such as communication skills training or performance evaluation. The aim of the current research is twofold: (1) to investigate whether off-the-shelf emotion recognition technology can detect social signals in media interviews and (2) to identify which combinations of social signals are most promising for evaluating trainees' performance in a media interview. To investigate this, non-verbal signals were automatically recognised from practice on-camera media interviews conducted within a media training setting with a sample size of 34. Automated non-verbal signal detection consists of multimodal features including facial expression, hand gestures, vocal behaviour and 'honest' signals. The on-camera interviews were categorised into effective and poor communication exemplars based on communication skills ratings provided by trainers and neutral observers which served as a ground truth. A correlation-based feature selection method was used to select signals associated with performance. To assess the accuracy of the selected features, a number of machine learning classification techniques were used. Naive Bayes analysis produced the best results with an F-measure of 0.76 and prediction accuracy of 78%. Results revealed that a combination of body movements, hand movements and facial expression are relevant for establishing communication effectiveness in the context of media interviews. The results of the current study have implications for the automatic evaluation of media interviews with a number of potential application areas including enhancing communication training including current media skills training.

Social Representations and Emotions

Abstract. A number of authors consider that exploring the interconnections between social representations and emotions is essential. However, both empirical and theoretical contributions have focused on specific aspects of these concepts and thus offer a narrow view of their articulation. Moreover, these are published in different languages, making it difficult to provide an overview of the current knowledge on the subject. Consequently, this article adopts a broader approach through a literature review articulating social representations and emotions. This is based on a search of various databases, conducted between March and April 2020 and using the terms “social representation” and “emotion” (or affect, mood, or feeling) in their singular and plural forms, both in French and in English. As a result, 41 references explicitly mentioned both terms and were published in English, French, Portuguese, and Spanish were collected. This brought to light two lines of inquiry that structure this field of research: the first focuses on the role of emotions in the emergence, dynamics, and functioning of social representations, while the second explores how social representations determine emotions or emotional processes. These perspectives will be discussed from both a theoretical and methodological standpoint with the aim of highlighting new avenues for research.

Neurotransmitters and Electrophysiological Changes Might Work as Biomarkers for Diagnosing Affective Disorders

Affective disorders are the leading causes of human disability worldwide; however, the diagnosis is still hard to define, because emotion is the least study subjects in psychology. Recent emotional studies suggest that human emotions are developed from basic emotions, which are evolved for fundamental human lives. Even though most psychologists agree upon the idea that there are some basic emotions, there is little agreement on how many emotions are basic, which emotions are basic, and why they are basic. In our previous papers, we suggested that there are three basic emotions: joy, fear, and disgust. These basic emotions depend on the peptides and monoamines: dopamine-joy (peptides-reward), norepinephrine-fear (anger), and serotonin-disgust (sadness). Further tests with event-related potentials (ERP) found that joy, fear, and disgust showed the fastest response compared with other emotions, suggesting that they are fast automatic responses, which confirmed that these three emotions are prototypical emotions. Other basic emotions, anger and sadness, are due to object induced behaviors instead of sensation of object, so they developed secondary to prototypical emotions. Thus, we concluded that only joy, fear, and disgust are prototypical emotions, which can mix into other emotions, like the primary colors. In all, the neural substrates for all emotions, including the affections, are possibly monoamine neuromodulators: joy-dopamine (peptides), fear (anger)-norepinephrine, and disgust-serotonin. We hope these basic emotional studies will offer some neural mechanisms for emotional processing and shed lights on the diagnosis of affective disorders.

On Facial Expression Recognition Benchmarks

Facial expression is an important form of nonverbal communication, as it is noted that 55% of what humans communicate is expressed in facial expressions. There are several applications of facial expressions in diverse fields including medicine, security, gaming, and even business enterprises. Thus, currently, automatic facial expression recognition is a hotbed research area that attracts lots of grants and therefore the need to understand the trends very well. This study, as a result, aims to review selected published works in the domain of study and conduct valuable analysis to determine the most common and useful algorithms employed in the study. We selected published works from 2010 to 2021 and extracted, analyzed, and summarized the findings based on the most used techniques in feature extraction, feature selection, validation, databases, and classification. The result of the study indicates strongly that local binary pattern (LBP), principal component analysis (PCA), saturated vector machine (SVM), CK+, and 10-fold cross-validation are the most widely used feature extraction, feature selection, classifier, database, and validation method used, respectively. Therefore, in line with our findings, this study provides recommendations for research specifically for new researchers with little or no background as to which methods they can employ and strive to improve.

Differential Hemispheric Lateralization of Emotions and Related Display Behaviors: Emotion-Type Hypothesis

There are two well-known hypotheses regarding hemispheric lateralization of emotions. The Right Hemisphere Hypothesis (RHH) postulates that emotions and associated display behaviors are a dominant and lateralized function of the right hemisphere. The Valence Hypothesis (VH) posits that negative emotions and related display behaviors are modulated by the right hemisphere and positive emotions and related display behaviors are modulated by the left hemisphere. Although both the RHH and VH are supported by extensive research data, they are mutually exclusive, suggesting that there may be a missing factor in play that may provide a more accurate description of how emotions are lateralization in the brain. Evidence will be presented that provides a much broader perspective of emotions by embracing the concept that emotions can be classified into primary and social types and that hemispheric lateralization is better explained by the Emotion-type Hypothesis (ETH). The ETH posits that primary emotions and related display behaviors are modulated by the right hemisphere and social emotions and related display behaviors are modulated by the left hemisphere.

Emotional Contagion: A Brief Overview and Future Directions

Social interactions can trigger emotional contagion between individuals resulting in behavioral synchrony. Emotional contagion can be a very effective and attractive strategy in communication and advertising, and understanding the mechanisms underlying emotional contagion can help marketers to improve their commercial approaches or develop better ones. The purpose of this study is to review and classify the various methodologies and theoretical approaches on emotional contagion, identify the best practices in this domain, and identify ways of gaging and measuring emotional contagion. The study is based on a mini literature review. We identify different mechanisms and approaches to emotional contagion described in the literature. Emotional contagion can be triggered by facial expressions, indirect human interactions, and/or by observing other people's behavior in direct and indirect interactions. Furthermore, emotional contagion can be triggered physiologically or neurologically by synchronizing with the emotional state of others during human interactions. Regarding the assessment and measurement of emotional contagion, we argue that methods based on neuroscience tools are much more accurate and effective than methods based on traditional research approaches. The study identifies guidelines for research on commercial communication through emotional contagion that can be especially interesting for academia and marketing practitioners. The findings are important for field marketers interested in developing new individualized approaches in their commercial strategies and marketing in general. In addition, the study can become the basis of research that further refines and compares the efficacy of the various techniques and tools involved.

Are All "Basic Emotions" Emotions? A Problem for the (Basic) Emotions Construct

Despite decades of challenges to the idea that a small number of emotions enjoys the special status of "basic emotions," the idea continues to have considerable influence in psychology and beyond. However, different theorists have proposed substantially different lists of basic emotions, which suggests that there exists no stable criterion of basicness. To some extent, the basic-emotions enterprise is bedeviled by an overreliance on English affective terms, but there also lurks a more serious problem-the lack of agreement as to what emotions are. To address this problem, three necessary conditions are proposed as a minimal requirement for a mental state to be an emotion. A detailed analysis of surprise, a widely accepted basic emotion, reveals that surprise violates even this minimal test, raising the possibility that it and perhaps other would-be basic emotions might not be emotions at all. An approach that combines ideas such as undifferentiated affect and cognitive appraisal is briefly proposed as a way of theorizing about emotions that is less dependent on the vagaries of language and incoherent notions of basic emotions. Finally, it is suggested that the perennial question of what an emotion is should be given more serious attention.

Are Emotions Natural Kinds After All? Rethinking the Issue of Response Coherence

The synchronized co-activation of multiple responses-motivational, behavioral, and physiological-has been taken as a defining feature of emotion. Such response coherence has been observed inconsistently however, and this has led some to view emotion programs as lacking biological reality. Yet, response coherence is not always expected or desirable if an emotion program is to carry out its adaptive function. Rather, the hallmark of emotion is the capacity to orchestrate multiple mechanisms adaptively-responses will co-activate in stereotypical fashion or not depending on how the emotion orchestrator interacts with the situation. Nevertheless, might responses cohere in the general case where input variables are specified minimally? Here we focus on shame as a case study. We measure participants' responses regarding each of 27 socially devalued actions and personal characteristics. We observe internal and external coherence: The intensities of felt shame and of various motivations of shame (hiding, lying, destroying evidence, and threatening witnesses) vary in proportion (i) to one another, and (ii) to the degree to which audiences devalue the disgraced individual-the threat shame defends against. These responses cohere both within and between the United States and India. Further, alternative explanations involving the low-level variable of arousal do not seem to account for these results, suggesting that coherence is imparted by a shame system. These findings indicate that coherence can be observed at multiple levels and raise the possibility that emotion programs orchestrate responses, even in those situations where coherence is low.

Applying Probabilistic Programming to Affective Computing

Affective Computing is a rapidly growing field spurred by advancements in artificial intelligence, but often, held back by the inability to translate psychological theories of emotion into tractable computational models. To address this, we propose a probabilistic programming approach to affective computing, which models psychological-grounded theories as generative models of emotion, and implements them as stochastic, executable computer programs. We first review probabilistic approaches that integrate reasoning about emotions with reasoning about other latent mental states (e.g., beliefs, desires) in context. Recently-developed probabilistic programming languages offer several key desidarata over previous approaches, such as: (i) flexibility in representing emotions and emotional processes; (ii) modularity and compositionality; (iii) integration with deep learning libraries that facilitate efficient inference and learning from large, naturalistic data; and (iv) ease of adoption. Furthermore, using a probabilistic programming framework allows a standardized platform for theory-building and experimentation: Competing theories (e.g., of appraisal or other emotional processes) can be easily compared via modular substitution of code followed by model comparison. To jumpstart adoption, we illustrate our points with executable code that researchers can easily modify for their own models. We end with a discussion of applications and future directions of the probabilistic programming approach.

The Psychological Pathway to Suicide Attempts: A Strategy of Control Without Awareness

Objectives

This paper aims to identify potential areas for refinement in existing theoretical models of suicide, and introduce a new integrative theoretical framework for understanding suicide, that could inform such refinements.

Methods

Literature on existing theoretical models of suicide and how they contribute to understanding psychological processes involved in suicide was evaluated in a narrative review. This involved identifying psychological processes associated with suicide. Current understanding of these processes is discussed, and suggestions for integration of the existing literature are offered.

Results

Existing approaches to understanding suicide have advanced the current knowledge of suicide in various ways. They have guided valuable research in the following areas: motivations for suicide and the psychological distress which influences suicide attempts; ambivalence about suicide; suicidal individuals’ focus of attention; and ways in which individuals who contemplate suicide differ from individuals who attempt suicide. We outline a new theoretical framework as a means to integrating all of these concepts into the three principles of control, conflict, and awareness. Within this framework, suicide is regarded as occurring due to a long standing conflict between an individual’s personal goals, culminating in an episode of acute loss of control. The new framework posits that the individual then strives to regain control through the means of suicide because of a narrowed awareness of consequences of their actions on other valued goals. This psychological mechanism of limited awareness is posited to be the common pathway by which individuals make a suicide attempt, regardless of which risk factors are present.

Conclusion

This article introduces a theoretical framework that generates several hypotheses for future research, and focuses on psychological processes occurring during immediate crisis. One of the key hypotheses resulting from our predictions on how individuals progress from contemplating to attempting suicide will be tested in an ongoing program of research: Individuals who attempt suicide have a significantly reduced awareness of consequences of suicide, which would negatively impact on their important life goals, values, principles, or ideals, compared to individuals who contemplate suicide. Therapy guided by the new framework may be more flexible, immediate, and client-focused than other therapies for suicidal individuals.

Expression Authenticity: The Role of Genuine and Deliberate Displays in Emotion Perception

People dedicate significant attention to others' facial expressions and to deciphering their meaning. Hence, knowing whether such expressions are genuine or deliberate is important. Early research proposed that authenticity could be discerned based on reliable facial muscle activations unique to genuine emotional experiences that are impossible to produce voluntarily. With an increasing body of research, such claims may no longer hold up to empirical scrutiny. In this article, expression authenticity is considered within the context of senders' ability to produce convincing facial displays that resemble genuine affect and human decoders' judgments of expression authenticity. This includes a discussion of spontaneous vs. posed expressions, as well as appearance- vs. elicitation-based approaches for defining emotion recognition accuracy. We further expand on the functional role of facial displays as neurophysiological states and communicative signals, thereby drawing upon the encoding-decoding and affect-induction perspectives of emotion expressions. Theoretical and methodological issues are addressed with the aim to instigate greater conceptual and operational clarity in future investigations of expression authenticity.

Covid-19 vaccines: A model of acceptance behavior in the healthcare sector

The emergence of Covid-19 has affected all aspects of human life across the globe. Lockdowns everywhere are having dramatic social and economic consequences. No therapy has yet been approved, and vaccines are a priority potential tool to control the pandemic and its impacts. Multiple vaccines are in the last stage of the development process, but part of the population is not willing to get vaccinated for Covid-19. Several studies have examined the percentage of the population willing to get vaccinated, but few have analyzed the reasons for their decision. In this context, researching the factors influencing individuals’ intention to use a potential Covid-19 vaccine will be important to public health strategies. This paper analyzes these factors with an adapted Cognitive-Affective-Normative (CAN) model. Perceived vaccine efficacy is used as a cognitive variable, fear of the vaccine and fear of Covid-19 are used as affective variables, and social influence is used as the normative variable. The proposed model strongly explains the intention to use the Covid-19 vaccine (R2 = 0.81). The results show that vaccine efficacy will be the most important determinant of Covid-19 vaccine acceptance, followed by social influence. The findings can be very helpful for public health policies aimed at achieving widespread vaccination, a must for vaccine success.

The Development of Emotion Reasoning in Infancy and Early Childhood

Historically, research characterizing the development of emotion recognition has focused on identifying specific skills and the age periods, or milestones, at which these abilities emerge. However, advances in emotion research raise questions about whether this conceptualization accurately reflects how children learn about, understand, and respond to others’ emotions in everyday life. In this review, we propose a developmental framework for the emergence of emotion reasoning—that is, how children develop the ability to make reasonably accurate inferences and predictions about the emotion states of other people. We describe how this framework holds promise for building upon extant research. Our review suggests that use of the term emotion recognition can be misleading and imprecise, with the developmental processes of interest better characterized by the term emotion reasoning. We also highlight how the age at which children succeed on many tasks reflects myriad developmental processes. This new framing of emotional development can open new lines of inquiry about how humans learn to navigate their social worlds.

Emotions in Twitter communication and stock prices of firms: the impact of Covid-19 pandemic

In this paper, we explored two key aspects of organization theory—organizational communication in the face of crisis and the influence of emotions expressed in social media communication and their impact on stock prices of firms. We extracted emotional content from 189,303 tweets and collected financial data for six quarters for 105 companies listed on the New York Stock Exchange from the Fortune 1000 list of companies. We operationalized a set of metrics to measure emotion in organizational tweets. Our analysis showed that the operationalized metrics to measure emotion expressed in organizational tweets were significant predictors of stock prices of firms. Further analysis showed a moderation effect of the crisis on the association between emotion expressed in organizational tweets and stock prices in the presence of control variables. The study provides a detailed analysis of constituent positive (happiness) and negative (anger, fear, and sadness) emotions in organizational tweets and their association with stock prices of firms. Practitioners and regulators may use the analysis and the metrics to assess organizational communication and better leverage Twitter for crisis response. This paper showcases organizational crisis response of Twitter and its financial impact.